A hybrid neural network and ARIMA model for water quality time series prediction

Accurate predictions of time series data have motivated the researchers to develop innovative models for water resources management. Time series data often contain both linear and nonlinear patterns. Therefore, neither ARIMA nor neural networks can be adequate in modeling and predicting time series...

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Veröffentlicht in:	Engineering applications of artificial intelligence 2010-06, Vol.23 (4), p.586-594
1. Verfasser:	Faruk, Durdu Oemer
Format:	Artikel
Sprache:	eng
Schlagworte:	Accuracy ARIMA Backpropagation Dissolution Hybrid model Mathematical models Neural networks Nonlinearity Time series Water quality Water temperature
Online-Zugang:	Volltext
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